Naslov
The novel paradigm for a decision support system of the aerial non-technical survey

Autori
Bajić, Milan ; Gold, Hrvoje ; Horvat, Marko ; Krtalić, Andrija ; Laura, Davor ; Muštra, Mario

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
17th International Symposium Mine Action 2021, Book of Papers / Markt, Katarina - Zagreb : Hrvatski centar za razminiranje - Centar za testiranje, razvoj i obuku (HCR-CTRO), 2021, 62-68

Skup
17th International Symposium Mine Action

Mjesto i datum
Novi Vinodolski, Hrvatska, 16.06.2021. - 18.06.2021

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Nije recenziran

Ključne riječi
aerial non-technical survey, DSS, UAV, secondary mine indicators, multi-criteria ranking, deep learning, recommender system, CROMAC

Sažetak
The industry of sensors and unmanned aerial systems (UAV) enables the advancement of detection of explosive objects (landmines, unexploded ordnance, improvised explosive devices) and the non-technical survey of areas contaminated by explosive threats. In the last ten years, dominates research and development of the direct detection of explosive devices versus detection of indirect indicators of the explosive threats on large areas in frame of civilian Non-Technical Survey (NTS). The impact of the mentioned phenomena is not used to its full potentials in the civilian domain of NTS. Although UAV technology can provide a large amount of data, interpretation of the data and the decision-making as an outcome of the interpretation are not developed yet. Between 1998 and 2020 many research and technology development projects on aerial NTS are realized. Some of them applied Decision Support System (DSS) paradigms: GIS-based DSS paradigm, Multi-Criteria-based DSS paradigm, Automatic Target Recognition (ATR) paradigm. The Scientific Council of HCR Center for testing, development, and training, initiated in December 2019 research and development of the Aerial Non- Technical Survey, based on UAV data acquisition, and a recommender system in its DSS functions. The proposed recommender system utilizes deep learning algorithms and collaborative filtering (CF) that rely on datasets containing selection preferences for different objects. DSS knowledge database will be based on ontologies to facilitate formal description of complex semantic structures, knowledge transfer, and reuse. The objects and preferences will be derived by fusion of features of secondary indicators, ranked by eigenvalues. The novel DSS will be implemented in the new Aerial Non-Technical Survey System which will be realized through projects by several partners. The operational validation will be done by CROMAC in mine suspected areas of Croatia.

Izvorni jezik
Engleski

Znanstvena područja
Geofizika, Računarstvo, Interdisciplinarne tehničke znanosti

POVEZANOST RADA